Flaminio Squazzoni is Full Professor of Sociology at the Department of Social and Political Sciences of the University of Milan and director of BEHAVE. He teaches “Sociology” to undergraduate students, “Behavioural Sociology” to master students and “Behavioural Game Theory” to PhD students. Untill November 2018, he has been Associate Professor of Economic Sociology at the Department of Economics and Management of the University of Brescia, where he led the GECS-Research Group on Experimental and Computational Sociology.

He is editor of JASSS-Journal of Artificial Societies and Social Simulation, co-editor of Sociologica -International Journal for Sociological Debate and member of the editorial boards of Research Integrity and Peer Review and Sistemi Intelligenti. He is advisory editor of the Wiley Series in Computational and Quantitative Social Science and the Springer Series in Computational Social Science and member of the advisory board of ING’s ThinkForward Initiative. He is former President of the European Social Simulation Association (Sept 2012/Sept 2016, since 2010 member of the Management Committee) and former Director of the NASP ESLS PhD Programme in Economic Sociology and Labour Studies (2015-2016).

I am an Associate Professor in the Department of Industrial Engineering at the University of Engineering and Technology Taxila, Pakistan. I hold a PhD in Industrial Engineering and have more than 20 years of academic experience in teaching, research, and student supervision.

My research focuses on industrial and systems engineering and data-driven decision analytics. It combines multi-criteria decision-making, agent-based modeling, simulation, optimization, and machine learning to examine complex decisions involving uncertainty, competing objectives, and multiple stakeholders. Applications include manufacturing, energy systems, sustainability, and organizational decision-making.

My published research includes assessments of hybrid energy policies, Industry 4.0 readiness, and sustainable cement production. I am also a coauthor of the peer-reviewed CoMSES computational model “Integrating Reinforcement Learning in Agent-Based Modeling for Dynamic Investment Decisions.” The associated 2026 journal article combines reinforcement learning, response surface methodology, and neural networks within an agent-based modeling framework. This work uses NetLogo simulations to investigate adaptive investment decisions under uncertainty.

My ongoing research and student supervision explore multi-agent reinforcement learning, large language models, and agent-based modeling for supply-chain decision support under disruptions. These activities extend my interests in adaptive decision-making and the analysis of complex industrial systems.

Alongside research, I teach undergraduate and graduate courses, supervise postgraduate research and undergraduate projects, and review manuscripts for scholarly journals. I welcome academic and industry research collaborations involving computational modeling, simulation experiments, decision-support systems, and sustainable industrial operations.